Although our reordering approach does improve the neural models, these more expressive models are still outperformed by the linear SVM with bag-of-embeddings representations. This is likely a side effect of the noise introduced by the bilingual embeddings. At test time, the model receives as input embeddings that are similar but not necessarily the same as at training. In the future, it may be helpful to develop models which are more robust to this noise, or alternatively to use low-resource machine translation techniques [1]}, [2]}, [3]}, [4]}
